Statistical Models In Toxicology And Biochemistry

毒理学和生物化学的统计模型

• 批准号: 6681947
• 负责人: Christopher J Portier
• 金额: --
• 依托单位: NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/6681947
• 关键词: biochemistry; cancer risk; cell cycle; chemical carcinogen; chemical carcinogenesis; dioxins; endocrinology; environmental contamination; environmental exposure; environmental toxicology; growth /development; immunology; laboratory rat; mathematical model; model design /development; neurology; pharmacology; statistics /biometry; thyroid hormones; vital statistics

This Project focuses on (1) The development of methodology for incorporating ?cutting-edge? research findings into future risk assessments; (2) The development of methods for designing studies to improve risk estimates, especially when mechanistic data is involved; (3) The development of methods for the evaluation of exposure, dose-response shape and potency; (4) The development of methods for evaluating mixtures when multiple mechanisms are involved; (5) The development of methods which harmonize cancer and non-cancer health risk assessments; (6) Direct engagement of the regulatory community through expert panels, peer review and collaborative research; (7) Practical improvement of stochastic processes through careful linkage of theoretical developments with computational methods that are accurate and convenient; (8) Collaboration with research groups within the NIEHS and research groups doing similar work to improve the biological understanding of disease incidence; (9) Iterative improvement of the biological basis for disease incidence models through a process of hypothesis testing and laboratory research; (10) Linkage of disease incidence models to toxicokinetics models in a scientifically credible manner; (11) Use of the broadest array of data in both the development of the model and its application; (12) Support of the National Toxicology Program. ? A comprehensive, biologically based mathematical model was developed for the rat estrus cycle. This model describes the endocrine signaling and feedback involved in 8 hormones which drive the estrus cycle: GnRH, LH, FSH, estradiol, dopamine, prolactin and progesterone. Seven organ systems controlling the production, use and degradation of these hormones are included in the model: brain/hypothalamus, hypophysial portal system, pituitary, blood, ovaries, liver and gastro-intestinal tract. ? Non-monotonic dose response (U-shaped) patterns occur when a toxic substance acts as a stimulant in small doses, but as an inhibitor in large doses. A mechanistically based mathematical model is introduced in this manuscript, and the ability of the model to demonstrate non-monotonic dose response is discussed. ? When Toxic Equivalkenct Factors (TEF;s) are defined in terms of ratios of ED50s between congeners, the other congener-specific dose-response parameters should be equal. If not, we cannot obtain a consistent definition of relative potency at every response level. Two enzymatic activity responses from exposure to several dioxin-like congeners were examined. Our analysis suggests that dose-response curves are quite different between congeners. ? The benchmark dose methodology has been proposed as a replacement for existing methods in health risk assessments. Researchers in LCBRA performed a critical assessment of the benchmark dose methodology looking at the stated goals for using this method relative to the actual practice in its application. It was found that choice of the response for which to calculate the benchmark dose had a critical impact on the degree to which curvature in the dose-response data is included in the analysis and using the lower bound as a point estimate was inappropriate. ? PBTK models for methyleugenol and anthraquinone have been upgraded. ? A model was developed using linked birth and death processes to describe the cell proliferation cycle for rat hepatocytes. The model was applied to a furan exposure experiment on mice and includes explicit modeling of mitotic cells, BrdU labeled cells, necrosis and apoptosis. ? An earlier PBPK model of enzyme induction by TCDD was expanded to represent pharmacodynamics of the Ah receptor, transcriptional activation, relation between length of the polyadenylate (polyA) tail and mRNA stability, and translation into protein. This model is the first dioxin model that reproduces both the short-term decline in Ah binding capacity on binding TCDD and the increase in binding capacity after long-term exposure. ? A PBPK model was constructed for exposure of rats to naphthalene. Two enantiomers of naphthalene oxide can be produced, and reproduction of the disposition data could only be achieved by using a different Vmax for production of each one. ? A new graph theoretical method for representing (as a form of flowchart) and analyzing networks of biochemical reaction was developed. ? We also work with other Federal agencies to evaluate risks of environmental pollutants (e.g., MTBE, 1,3-butadiene, TCDD) and to develop approaches for incorporating basic science into the risk assessment process (e.g., TCDD, endocrine disruptors, peroxisome proliferators). Through membership on the NIEHS Toxicokinetics Faculty, the Chemical Nominations Faculty, and Review Group-1 of the Report on Carcinogens (RoC), we contribute to the review of chemicals nominated to NTP, the design of new studies, and the review of evidence on chemicals nominated for listing or delisting in the RoC. ? NASA and NIEHS have a joint research project to assess the health effects of combined exposures to climatic and environmental factors. ? A method was developed for estimating the initial concentration of cDNA amplicon in a PCR process.

本项目着重于(1)发展整合前沿技术的方法。对未来风险评估的研究结果；(2)发展设计研究的方法，以改进风险估计，特别是在涉及机械数据时；(3)开发评估暴露、剂量反应形状和效力的方法；(4)在涉及多种机制的情况下，开发评估混合物的方法；(5)制订协调癌症和非癌症健康风险评估的方法；(6)监管界通过专家小组、同行评审和合作研究直接参与；(7)通过将理论发展与精确和方便的计算方法仔细联系起来，对随机过程进行实际改进；(8)与NIEHS内的研究小组和从事类似工作的研究小组合作，以提高对疾病发病率的生物学认识；(9)通过假设检验和实验室研究，不断完善疾病发病率模型的生物学基础；（10）以科学可信的方式将疾病发生率模型与毒物动力学模型联系起来；（11）在模型的发展和应用中使用最广泛的数据；（12）国家毒理学计划的支持。